Quantification of clay content using the transient electromagnetic and spectral induced polarization method

2021 ◽  
Author(s):  
Lukas Aigner ◽  
Timea Katona ◽  
Hadrien Michel ◽  
Arsalan Ahmed ◽  
Thomas Hermans ◽  
...  
Keyword(s):  
Grain Size ◽  
Critical Role ◽  
Clay Content ◽  
Induced Polarization ◽  
Single Frequency ◽  
Time Range ◽  
Data Set ◽  
Transient Electromagnetic ◽  
Spectral Induced Polarization ◽  
Imaging Results

<p>Detailed information on the clay content of the subsurface and its spatial distribution plays a critical role in the interaction between surface- and groundwater. In this study, we investigate a new methodology to integrate data measured with electromagnetic and electrical geophysical methods, namely, the transient electromagnetic (TEM) and the spectral induced polarization (SIP) to quantify subsurface clay content in an imaging framework. The methodology is tested in data sets collected at a quarry close to Vienna and consists of a ca. 10 m thick clay layer below a ca. 8 m thick overburden of sandy silts. Our data set includes SIP data collected along a 315 m long profile with an electrode separation of 5 m in a frequency range from 0.1 to 225 Hz. Along this profile, we measured 26 TEM soundings using a 12.5 m loop with 24 windows recording in a time range between 4 and 140 μs. Ground truth information corresponds to grain size analysis conducted in 25 soil samples collected in a depth from 5 to 28 m. SIP inversion results at a single frequency provided structural a-priori information to improve the inversion of the TEM data. The inverted TEM conductivity model, nearest to the position of soil sample collection, was correlated to the grain size distribution and the resulting positive exponential relationship was used to obtain vertical 1D variations of clay content with depth. All sounding positions were interpolated to obtain a 2D image of subsurface clay content. This clay content variations were then compared to images of the Cole-Cole parameters, describing the frequency dependence of SIP imaging results. To evaluate the uncertainty in our clay estimations, we applied the Bayesian evidential learning 1D imaging (BEL1D). We obtained uncertainties of layer thickness, resistivity, and clay content by integrating the clay-conductivity relationship derived from TEM data into the BEL1D framework.</p>

Determining frequency dependence of carbon turnover in peat using spectral induced polarization

2021 ◽  
Author(s):  
Timea Katona ◽  
Benjamin Gilfedder ◽  
Sven Frei ◽  
Lukas Aigner ◽  
Matthias Bücker ◽  
...  
Keyword(s):  
Frequency Dependence ◽  
Iron Oxides ◽  
Induced Polarization ◽  
Electrode Spacing ◽  
Electrode Polarization ◽  
Biogeochemical Processes ◽  
Carbon Turnover ◽  
Spectral Induced Polarization ◽  
Polarization Response ◽  
Imaging Results

<p>Our study discusses imaging results from a spectral induced polarization (SIP) survey to identify concurring processes (such as aerobic respiration, denitrification, or sulfate- and iron reduction) in a biogeochemically active peat in a wetland located in the Lehstenbach catchment in Southeastern Germany. Terrestrial wetland ecosystems such as peatlands are a critical element in the global carbon cycle. Due to their role as natural carbon sinks and ecological importance for an array of flora and fauna, there is a growing demand to conserve and restore degraded peatlands. Biogeochemical processes occur with non-uniform reaction rates within the peat, making the environment sensitive to physical disturbances. To investigate biogeochemical processes in-situ, it is important to avoid disturbing the redox-sensitive conditions in the subsurface by bringing oxygen into anoxic areas.  Our previous study demonstrated that the induced polarization (IP) was able to identify biogeochemically active and inactive areas of the peat. The IP response was sensitive to the presence of carbon turnover and P release in the absence of iron sulfide. These highly polarizable areas have high iron concentrations, but most likely in an oxidized form. As most iron oxides are poor conductors, the strong polarization response is unlikely related to an electrode polarization process.</p><p>Here we also analyzed the frequency dependence of the SIP data to investigate whether iron oxides and carbon-iron complexes, two possible mechanisms for the high polarization response, can be distinguished. SIP imaging data sets covered the frequency range between 0.06 and 225 Hz and were collected with varying electrode spacing (20 and 50 cm) at different locations within the Waldstein catchment characterized by different properties, e.g., saturated and non-saturated soils. Our imaging results reveal variations of the IP effect within the peat layer, indicating substantial heterogeneities in the peat composition and biogeochemical activity. The frequency dependence allowed us to resolve a sharper contrast between the different features of the peat. Geochemical analyses on a freeze core and pore water samples are used to validate our results and find correlations between the Cole-Cole parameters of the SIP response and the geochemical parameters.</p>

scholarly journals Experimental Study of Spectral Induced Polarization Response Based on Laboratory Measurement

2018 ◽  
Vol 16 (2) ◽  
pp. 25
Author(s):  
Dicky Ahmad Zaky ◽  
Suparwoto Suparwoto
Keyword(s):  
Experimental Study ◽  
Grain Size ◽  
Measurement System ◽  
Test Sample ◽  
Induced Polarization ◽  
Spectral Parameters ◽  
Digital Oscilloscope ◽  
Spectral Induced Polarization ◽  
Voltage Amplifier ◽  
Size Model

The spectral induced polarization (SIP) method can provide apparent complex resistivity based on measurements of multi frequency. SIP method also can provide more detail information about physical properties of rocks and minerals because SIP can give spectral parameters or Cole-Cole parameters such as, changeability (m), time constant (τ) and frequency dependence (c). An Experimental study in laboratory has been conducted to knowing the SIP response of some test sample. The measurement system is built with digital oscilloscope Pico ADC-100 as device for sampling the input and output voltage. Amplifier is used to doubled up the signal and input differential. The range frequency of measurement is 10−2 Hz - 103 Hz. Porouspot Cu − CuSO4 is used to minimize the polarization at potential electrode. A Matlab listings is used to calculate the response of impedance and phase. The result from calibration that used the parallel circuit RC indicate that the measurement system was good. SIP response of porous model indicate that the response form an asymptotic resistivity, and the peak of phase is in the range frequency where the dispersion happen. The result also indicate that resistivity of small grain size model is larger than the big grain size model. Result from sample of mineralized rocks did not indicate a perfect SIP response, it is influenced by the contact between mineral and water was minimum.

Aftereffects in the Transient Electromagnetic Method: Inductively Induced Polarization

2021 ◽  
Vol 62 (12) ◽  
pp. 1440-1448
Author(s):  
N.O. Kozhevnikov ◽  
E.Yu. Antonov
Keyword(s):  
Transient Response ◽  
Electric Polarization ◽  
Induced Polarization ◽  
Point Of View ◽  
Electromagnetic Method ◽  
Time Range ◽  
General Point ◽  
Transient Electromagnetic Method ◽  
Transient Electromagnetic ◽  
Tem Method

Abstract —Inductively induced electric polarization (IIP) is one of the aftereffects inherent in the geologic materials and affecting results of the transient electromagnetic method. Its effect on the inductive transient response manifests itself as a nonmonotonic EMF decay, including the polarity reversal. The dependence of IIP on many conditions makes it difficult to study the basic regularities in its manifestation. One of the ways to address this problem is to present the simulation results as a normalized transient response. From the most general point of view, the intensity and time range of the IIP manifestation are controlled by the competition between induction and induced polarization phenomena. Induced polarization manifests itself differently, depending on the transmitter used for the excitation of the ground response. Therefore, when studying polarizable ground, the results of the conventional IP method and those of the TEM method do not always correlate.

scholarly journals Impact of controlled changes in grain size and pore space characteristics on the hydraulic conductivity and spectral induced polarization response of "proxies" of saturated alluvial sediments

2010 ◽  
Vol 7 (4) ◽  
pp. 6057-6080 ◽  
Author(s):  
K. Koch ◽  
A. Kemna ◽  
J. Irving ◽  
K. Holliger
Keyword(s):  
Grain Size ◽  
Hydraulic Conductivity ◽  
Pore Space ◽  
Groundwater Resources ◽  
Fine Sand ◽  
Induced Polarization ◽  
Alluvial Deposits ◽  
Spectral Induced Polarization ◽  
Industrial Grade ◽  
Granulometric Characteristics

Abstract. Understanding the influence of pore space characteristics on the hydraulic conductivity and spectral induced polarization (SIP) response is critical for establishing relationships between the electrical and hydrological properties of surficial unconsolidated sedimentary deposits, which host the bulk of the world's readily accessible groundwater resources. Here, we present the results of laboratory SIP measurements on industrial-grade, saturated quartz samples with granulometric characteristics ranging from fine sand to fine gravel, which can be regarded as proxies for widespread alluvial deposits. We altered the pore space characteristics by changing (i) the grain size spectra, (ii) the degree of compaction, and (iii) the level of sorting. We then examined how these changes affect the SIP response, the hydraulic conductivity, and the specific surface area of the considered samples. In general, the results indicate a clear connection between the SIP response and the granulometric as well as pore space characteristics. In particular, we observe a systematic correlation between the hydraulic conductivity and the relaxation time of the Cole-Cole model describing the observed SIP effect for the entire range of considered grain sizes. The results do, however, also indicate that the detailed nature of these relations depends strongly on variations in the pore space characteristics, such as, for example, the degree of compaction. The results of this study underline the complexity of the origin of the SIP signal as well as the difficulty to relate it to a single structural factor of a studied sample, and hence raise some fundamental questions with regard to the practical use of SIP measurements as site- and/or sample-independent predictors of the hydraulic conductivity.

scholarly journals The Application of Spectral Induced Polarization to Determination of Hydraulic Conductivity

2021 ◽  
Author(s):  
◽  
Sheen Joseph
Keyword(s):  
Grain Size ◽  
Relaxation Time ◽  
New Zealand ◽  
Hydraulic Conductivity ◽  
Time Constant ◽  
Coastal Aquifers ◽  
Induced Polarization ◽  
Pore Fluid ◽  
Relaxation Time Constant ◽  
Spectral Induced Polarization

<p>Spectral Induced Polarization (SIP) is a geophysical technique that measures the frequency dependence of the electrical conductivity of a material. This thesis is an attempt to investigate the potential of using SIP as a proxy to predict the hydraulic conductivity of New Zealand shallow coastal aquifers. SIP measurements were made on sand samples that are typical of New Zealand coastal aquifers with a custom built impedance spectrometer and sample holder allowing the measurement of a phase difference as small a milliradian.  Even though the relaxation time shows a small dependence on pore fluid conductivity, especially at lower pore fluid conductivities, this variation is not serious enough to affect the hydraulic conductivity estimation at the field scale, but could be significant in the investigation of mechanisms that cause polarization in porous media.  Measurements on sieved fractions of sand established that there is an excellent correlation between the Cole-Cole relaxation time constant and grain size. The Cole-Cole relaxation time constant is very sensitive to the grain size distribution. Hydraulic conductivity predictions were attempted using various existing models. While the results are encouraging, it looks like there may not be a single universal model to predict hydraulic conductivity using SIP response.  When a correction term in the form of a multiplication constant is used, all the tested models seem to make very good predictions. But the constants calculated by fitting to the measured data could be applicable only to the type of materials studied. The dependence of the existing models on quantities like counterion diffusion coefficient, electrical formation factor and porosity makes hydraulic conductivity prediction challenging as these quantities are difficult to measure accurately in a field setting. Nevertheless it is concluded that SIP can be successfully applied to study hydraulic conductivity of New Zealand shallow coastal aquifers.</p>

scholarly journals An experiment of spectral induced polarization

1994 ◽  
Vol 37 (5 Sup.) ◽  
Author(s):  
B. Balia ◽  
G. P. Deidda ◽  
A. Godio ◽  
G. Ranieri ◽  
L. Sambuelli ◽  
...  
Keyword(s):  
Grain Size ◽  
Apparent Resistivity ◽  
Mineral Content ◽  
Test Site ◽  
Induced Polarization ◽  
Mineral Deposits ◽  
Axial Dipole ◽  
Spectral Induced Polarization ◽  
And Inversion ◽  
Phase Spectra

A Spectral Induced Polarization (SIP) survey was carried out in a mining test site in Sardinia (Italy). Measurements were developed along a profile by using an axial dipole-dipole array with 10 AB positions and 6 MN positions for cach AB. The amplitude and phase spectra of the apparent resistivity were acquired in the 0.25-4096 Hz frequeney range. The results obtained through the processing and inversion step seem to confirm that, with respect to the classical TD/FD Induced Polarization, SIP allows better discrimination of some important characteristics of mineral deposits such as mineral content and grain size.

scholarly journals Impact of changes in grain size and pore space on the hydraulic conductivity and spectral induced polarization response of sand

2011 ◽  
Vol 15 (6) ◽  
pp. 1785-1794 ◽  
Author(s):  
K. Koch ◽  
A. Kemna ◽  
J. Irving ◽  
K. Holliger
Keyword(s):  
Grain Size ◽  
Hydraulic Conductivity ◽  
Pore Space ◽  
Groundwater Resources ◽  
Fine Sand ◽  
Induced Polarization ◽  
Spectral Induced Polarization ◽  
Industrial Grade ◽  
Granulometric Characteristics ◽  
Cole Model

Abstract. Understanding the influence of pore space characteristics on the hydraulic conductivity and spectral induced polarization (SIP) response is critical for establishing relationships between the electrical and hydrological properties of surficial unconsolidated sedimentary deposits, which host the bulk of the world's readily accessible groundwater resources. Here, we present the results of laboratory SIP measurements on industrial-grade, saturated quartz samples with granulometric characteristics ranging from fine sand to fine gravel. We altered the pore space characteristics by changing (i) the grain size spectra, (ii) the degree of compaction, and (iii) the level of sorting. We then examined how these changes affect the SIP response, the hydraulic conductivity, and the specific surface area of the considered samples. In general, the results indicate a clear connection between the SIP response and the granulometric as well as pore space characteristics. In particular, we observe a systematic correlation between the hydraulic conductivity and the relaxation time of the Cole-Cole model describing the observed SIP effect for the entire range of considered grain sizes. The results do, however, also indicate that the detailed nature of these relations depends strongly on variations in the pore space characteristics, such as, for example, the degree of compaction. This underlines the complexity of the origin of the SIP signal as well as the difficulty to relate it to a single structural factor of a studied sample, and hence raises some fundamental questions with regard to the practical use of SIP measurements as site- and/or sample-independent predictors of the hydraulic conductivity.

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